Robust Liver Steatosis Quantification Using Photon-Counting CT in Comparison to PDFF: Validation across Protocols and Cohorts.

Authors

Xinxin Xu, Jie Yuan, Xinxin Cai, Rong Deng, Jingzhe Li, Xinyu Wu, Huanhuan Chong, Haihong Ma, Yuchen Yang, Yongjun Chen, Zhihan Xu, Bernhard Schmidt, Markus Juergens, Haipeng Dong, Rui Chang, Weixia Li, Ruokun Li, Fuhua Yan, Huimin Lin

Published in

Academic radiology. Sep 07, 2026. Epub Sep 07, 2026.

Abstract

To evaluate the robustness and grading performance of Photon-counting CT (PCCT)-derived fat fraction (CTFF) in liver fat quantification across different protocols and cohorts with varying liver conditions, using proton density fat fraction (PDFF) as the reference.
The prospective study enrolled 297 participants in the Volunteer cohort. Participants were randomly assigned to 120-kVp or 140-kVp groups and subdivided into high- and low-dose subgroups for technical validation. Clinical validation was performed in two cohorts: participants with metabolic dysfunction-associated steatotic liver disease (MASLD, n = 86) and heterogeneous liver diseases (HLD, n = 61). PCCT and PDFF (reference standard for grading) were performed within 1 month. Statistical analyses included intraclass correlation coefficients, Bland-Altman analysis, Mann-Whitney U and Kruskal-Wallis tests, and areas under the receiver operating characteristic (AUC-ROC) and precision-recall curves (AUC-PR).
Overall, 444 participants were included (age 44.9 ± 14.3 years; 264 men). In the Volunteer cohort, CTFF showed excellent agreement with PDFF (all ICCs = 0.98; R² ≥0.96) with a maximum bias of 0.80% (95% CI: 0.70-0.89%), across the whole-cohort and subgroups. No significant differences in the absolute error between PDFF and CTFF were observed across all subgroups (all p > 0.05). CTFF achieved high diagnostic accuracy for both the detection and grading of steatosis with all AUC-ROC and AUC-PR exceeding 0.99. The diagnostic accuracy of CTFF was verified in the MASLD and HLD cohorts.
CTFF demonstrated excellent agreement with PDFF and consistent diagnostic performance across diverse scan settings and liver conditions.

PMID:
42705927
Bibliographic data and abstract were imported from PubMed on 08 Sep 2026.

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